/MonoDGP

The offical implementation of 'MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error Priors'

Primary LanguagePython

MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error Priors

The official results in the paper:

Models Val, AP3D|R40
Easy Mod. Hard
MonoDGP 30.7624% 22.3421% 19.0144%

New and better results in this repo:

Models Val, AP3D|R40 Logs Ckpts
Easy Mod. Hard
MonoDGP 30.9663% 22.4953% 19.9641% log ckpt
30.7194% 22.6883% 19.4441% log ckpt
30.1314% 22.7109% 19.3978% log ckpt

We also provide a new ckpt pretrained on the trainval set, you can directly utilize this ckpt and submit test results to the KITTI 3D object detection benchmark to verify our method.

Models Test, AP3D|R40 Ckpts Results
Easy Mod. Hard
MonoDGP 26.12% 18.87% 16.79% ckpt data

Test results submitted to the official KITTI Benchmark:

Car category:

All categories:

Installation

  1. Clone this project and create a conda environment:

    git clone https://github.com/PuFanqi23/MonoDGP.git
cd MonoDGP

conda create -n monodgp python=3.8
conda activate monodgp

  2. Install pytorch and torchvision matching your CUDA version:

    # For example, We adopt torch 1.9.0+cu111
pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html

  3. Install requirements and compile the deformable attention:

    pip install -r requirements.txt

cd lib/models/monodgp/ops/
bash make.sh

cd ../../../..

  4. Make dictionary for saving training losses:

    mkdir logs

  5. Download KITTI datasets and prepare the directory structure as:

    │MonoDGP/
├──...
│data/kitti/
├──ImageSets/
├──training/
│   ├──image_2
│   ├──label_2
│   ├──calib
├──testing/
│   ├──image_2
│   ├──calib

    You can also change the data path at "dataset/root_dir" in configs/monodgp.yaml.

Get Started

Train

You can modify the settings of models and training in configs/monodgp.yaml and indicate the GPU in train.sh:

bash train.sh configs/monodgp.yaml > logs/monodgp.log

Test

The best checkpoint will be evaluated as default. You can change it at "tester/checkpoint" in configs/monodgp.yaml:

bash test.sh configs/monodgp.yaml

Acknowlegment

This repo benefits from the excellent work MonoDETR.